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AI vs AI: Agent hacked McKinsey's chatbot and gained full read-write access in just two hours

An AI agent conducting a red-team exercise exploited an SQL injection flaw in McKinsey's Lilli AI platform, gaining full read-write access to its production database and exposing millions of plaintext chat messages and confidential files. The attack vector was an unauthenticated endpoint, and the agent achieved this in two hours without prior credentials. McKinsey patched the vulnerability within hours of disclosure by taking the development environment offline and blocking public API documentation, with no evidence of malicious data access.
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Security 1 AI vs AI: Agent hacked McKinsey's chatbot and gained full read-write access in just two hours 1 David and Goliath…but with AI agents Jessica Lyons Mon 9 Mar 2026 // 22:22 UTC Researchers at red-team security startup CodeWall say their AI agent hacked McKinsey's internal AI platform and gained full read and write access to the chatbot in just two hours. It's yet another indicator that agentic AI is becoming a more effective tool for conducting cyberattacks, including those against other AI systems. This attack wasn’t conducted with malicious intent. However, threat hunters tell us that miscreants are increasingly using agents in real-world attacks, indicating that machine-speed intrusions aren't going away. McKinsey, a mega-management consultancy that specializes in gnarly strategy work for huge corporations and governments, rolled out its generative AI platform called Lilli in July 2023. According to the company, 72 percent of its employees – that's upwards of 40,000 people – now use the chatbot, which processes more than 500,000 prompts every month. CodeWall uses AI agents to continuously attack customers' infrastructure, to help them improve their security posture. According to the startup, its own security agent suggested targeting McKinsey, citing the consulting company's public responsible disclosure policy and recent updates to Lilli. "So we decided to point our autonomous offensive agent at it," the researchers wrote in a Monday blog, noting that the agent didn't have access to any credentials for McKinsey’s assets. CodeWall’s researchers claim that within two hours of starting their red team raid, they achieved full read and write access to the entire production database and were able to access 46.5 million chat messages about strategy, mergers and acquisitions, and client engagements, all in plaintext, along with 728,000 files containing confidential client data, 57,000 user accounts, and 95 system prompts controlling the AI's behavior. These prompts were all writable, meaning an attacker could poison everything Lilli spits out to all of the tens of thousands of consultants using the chatbot. CodeWall's agent found the SQL injection flaw at the end of February, and the researchers disclosed the full attack chain on March 1. By the following day, McKinsey had patched all unauthenticated endpoints, taken the development environment offline, and blocked public API documentation. A McKinsey spokesperson told The Register that it fixed all of the issues identified by CodeWall within hours of learning about the problems. "Our investigation, supported by a leading third-party forensics firm, identified no evidence that client data or client confidential information were accessed by this researcher or any other unauthorized third party," the spokesperson told us. "McKinsey's cybersecurity systems are robust, and we have no higher priority than the protection of client data and information we have been entrusted with." AI vs AI CodeWall CEO Paul Price declined to tell us the exact prompts his team used to exploit the chatbot, but said the entire process was "fully autonomous from researching the target, analyzing, attacking, and reporting." The CodeWall agent initially gained access to Lilli after finding publicly exposed API documentation, including 22 endpoints that didn't require authentication. One of these wrote user search queries, and the agent found that the JSON keys (these are the field names) were concatenated into SQL and vulnerable to SQL injection. "When it found JSON keys reflected verbatim in database error messages, it recognised a SQL injection that standard tools wouldn't flag," the researchers wrote, adding that the error messages eventually began outputting live production data. It gets worse: Lilli's system prompts were stored in the same database, which gave the agent access to these as well. AI agents now help attackers, including North Korea, manage their drudge work Microsoft Azure CTO set Claude on his 1986 Apple II code, says it found vulns Malware-laced OpenClaw installers get Bing AI search boost OpenAI says Chinese cops used ChatGPT to plan and track smear ops against opponents Because the SQL injection flaw was read and write, an attacker could abuse this to silently rewrite Lilli's prompts, thus poisoning how the chatbot answered consultants' queries, what guardrails it followed, and how it cited sources. "No deployment needed," the blog says. "No code change. Just a single UPDATE statement wrapped in a single HTTP call." These security holes are now closed – but the larger threat remains, Price told The Register . "We used a specific AI research agent to autonomously select the target, it did this without zero human input," he said. "Hackers will be using the same technology and strategies to attack indiscriminately, with a specific objective in mind," such as "financial blackmail for data loss or ransomware." ® Share More about AI Security More like these × More about AI Security Narrower topics 2FA Advanced persistent threat AIOps Application Delivery Controller Authentication BEC Black Hat BSides Bug Bounty Center for Internet Security CHERI CISO Common Vulnerability Scoring System Cybercrime Cybersecurity Cybersecurity and Infrastructure Security Agency Cybersecurity Information Sharing Act Data Breach Data Protection Data Theft DDoS DeepSeek DEF CON Digital certificate Encryption End Point Protection Exploit Firewall Gemini Google AI Google Project Zero GPT-3 GPT-4 Hacker Hacking Hacktivism Identity Theft Incident response Infosec Infrastructure Security Kenna Security Large Language Model Machine Learning MCubed NCSAM NCSC Neural Networks NLP Palo Alto Networks Password Personally Identifiable Information Phishing Quantum key distribution Ransomware Remote Access Trojan Retrieval Augmented Generation REvil RSA Conference Software Bill of Materials Spamming Spyware Star Wars Surveillance Tensor Processing Unit TLS TOPS Trojan Trusted Platform Module Vulnerability Wannacry Zero trust Broader topics Self-driving Car More about Share 1 COMMENTS More about AI Security More like these × More about AI Security Narrower topics 2FA Advanced persistent threat AIOps Application Delivery Controller Authentication BEC Black Hat BSides Bug Bounty Center for Internet Security CHERI CISO Common Vulnerability Scoring System Cybercrime Cybersecurity Cybersecurity and Infrastructure Security Agency Cybersecurity Information Sharing Act Data Breach Data Protection Data Theft DDoS DeepSeek DEF CON Digital certificate Encryption End Point Protection Exploit Firewall Gemini Google AI Google Project Zero GPT-3 GPT-4 Hacker Hacking Hacktivism Identity Theft Incident response Infosec Infrastructure Security Kenna Security Large Language Model Machine Learning MCubed NCSAM NCSC Neural Networks NLP Palo Alto Networks Password Personally Identifiable Information Phishing Quantum key distribution Ransomware Remote Access Trojan Retrieval Augmented Generation REvil RSA Conference Software Bill of Materials Spamming Spyware Star Wars Surveillance Tensor Processing Unit TLS TOPS Trojan Trusted Platform Module Vulnerability Wannacry Zero trust Broader topics Self-driving Car TIP US OFF Send us news

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